The key part you highlight is that of hiring. If you want to be scale ready from day 1, you may not find the scale out talent because they either are working on

The key part you highlight is that of hiring. If you want to be scale ready from day 1, you may not find the scale out talent because they either are working on large scale problems or would want to work on large scale problems. In your early days, you are mostly hunting for a product market fit.So your problem statement will not even be relevant to the hires. This is the best case, the worst case is that the scale out thinking hampers your product market fit progress. That's the risk you run. So, while it seems to have gone scale out on day 1 in hindsight, it's always always better to start small and scale out as needs arise, even if that means re-architecting the whole stack. It's painful, but doable. It's also a reasonable challenge to entice new hires. You have scaled out a system from degree 1 to degree m. Now scale that out from m to r++. Something like that.